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Puducherry govt to file review petition in SC over BJP MLAs decision

Devdiscourse News Desk puducherry Last Updated at 08-12-2018 19:34:30 IST India
Puducherry govt to file review petition in SC over BJP MLAs decision
  • Chief Minister V Narayanasamy

The Puducherry government Saturday said it would file a review petition in the Supreme Court on its recent verdict, upholding the Centre's nomination of three BJP legislators as members of the assembly.

"The Apex court has delivered its verdict, upholding the nomination of three members to the Legislative Assembly. The government will file a review petition on the matter after

consulting legal experts," Chief Minister V Narayanasamy told reporters here.

Lt Governor Kiran Bedi had administered the oath of office to the three members, V Saminathan, K G Shankar and S Selvaganapathi,in her chamber on July 4, 2017, but Speaker V Vaithilingam declined to recognise them as MLAs and had cancelled their nomination.

The issue had intensified the rift between Bedi and the Congress government. with the latter assailing her action as unconstitutional and contending that the Centre had 'unilaterally' nominated the MLAs without consulting the territorial government.

The MLAs then challenged the Speakers' action and moved the Madras High Court, which upheld their nomination. Later, the Congress leaders filed an appeal in the Supreme Court, which upheld the Centre's decision.

Bedi had on December 6 welcomed the apex court verdict, saying she was "exceedingly grateful and happy" with the judgment.

On the contentious Mekedatu dam issue, Narayanasamy said that the government had filed a petition Friday in the Supreme Court, seeking a direction to the Centre to withdraw its approval for preparing a Detailed Project Report on the proposed dam across the Cauvery river in Karnataka.

He charged the Centre and the Karnataka governments with taking 'injurious steps' to construct the dam, saying it would hit riparian states dependent on the Cauvery, as also

Puducherry, "which will suffer a lot`.

(With inputs from agencies.)

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